Radar HRRP target recognition based on Gradient Boosting Decision Tree

Suixue Wang, Jinbing Li, Yanhua Wang, Yang Li

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

19 Citations (Scopus)

Abstract

Radar High Resolution Range Profile (HRRP) represents the radial distribution of target scattering centers on radar line of sight, which infers something about target structure signatures. In this paper, the method of HRRP target recognition based on Gradient Boosting Decision Tree (GBDT) is proposed and the method how to choose model parameters is investigated. The experimental results from measurement data have shown that GBDT can achieve better recognition results and high calculation efficiency than SVM and Naive Bayes classifier.

Original languageEnglish
Title of host publicationProceedings - 2016 9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1013-1017
Number of pages5
ISBN (Electronic)9781509037100
DOIs
Publication statusPublished - 13 Feb 2017
Event9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2016 - Datong, China
Duration: 15 Oct 201617 Oct 2016

Publication series

NameProceedings - 2016 9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2016

Conference

Conference9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2016
Country/TerritoryChina
CityDatong
Period15/10/1617/10/16

Keywords

  • gradient boosting decision tree
  • high resolution range profile
  • target recognition

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